HSE Graduate’s AI Project Wins at TECH & AI Awards
Daria Davydova, graduate of the HSE Graduate School of Business and Head of the AI Implementation Unit at the Artificial Intelligence Department of Alfa-Bank, received a prize at the TECH & AI Awards. She was awarded for the best AI solution for optimising business processes. The winners were determined as part of the VII Russian Summit and Awards on Digital Transformation (CDO/CDTO Summit & Awards).
The project ‘Intelligent Automation: The Synergy of Gen-AI and RPA for the Transformation of Alfa-Bank's Operational Activities’ won in the category of ‘Best AI Solution for Optimising Business Processes and Increasing Operational Productivity’ and received the Grand Prix of the award.
The VII Russian Summit on Digital Transformation of Organisations is a professional platform that unites representatives of business, technology companies, and the expert community. The participants discuss digitalisation practices, the implementation of artificial intelligence, and solutions that enable companies to increase efficiency and transform operational models.
As part of the summit, the organisers annually hold the TECH & AI Awards aimed at supporting and recognising organisations that implement advanced technological and AI solutions. The top award—the Grand Prix—is awarded to developers, companies, and executives who have made a significant contribution to the development of new technologies and artificial intelligence.
The project, which Daria Davydova (graduate of the GSB Master's in Operational Excellence and Production Systems) worked on, is aimed at developing infrastructure for creating AI agents based on the RPA and AlfaGen platforms. These solutions allow users to automate operational processes and increase their efficiency.
One of the key examples is an AI agent for currency control. Previously, specialists needed up to two hours to analyse one contract and fill in 90 fields, but now an agent performs this work in one minute. The agent automatically extracts the data, checks the document for compliance with the requirements, and forms a conclusion. The accuracy of automatic conclusions reached 80%, compared with the planned target of 60%. The system also retains the ability to process up to 2,700 contracts per day, which frees up experts to work with more complex tasks. By the end of 2026, Alfa-Bank plans to introduce a full-fledged multi-agent system for currency control.
Daria Davydova
‘I am proud of the projects that my team and I implement at Alfa-Bank. The modern world is changing rapidly, and new tools such as artificial intelligence open up opportunities for us to improve productivity. It's nice to see that our professional community also appreciates our efforts,’ said Daria Davydova.
Gregory Baev
‘Today, operational efficiency is relevant not only in industry, factories, and mines, but also in new industries: fintech, IT, and telecom. Daria Davydova's victory demonstrates that graduates of our programme can implement projects that not only meet current business needs, but also set new standards for operational management,’ said Gregory Baev, Academic Supervisor of the Operational Excellence and Production Systems programme.
The results of the award reflect the growing role of AI solutions in the transformation of business processes and in shaping the technology development agenda in the corporate environment. In light of this, there is an increasing demand for specialists capable of developing and implementing such solutions, which is exactly what HSE educational programmes are focused on.
See also:
HSE Scientists Develop Method to Compress Large Language Models Without Losing Quality
Researchers from the AI and Digital Science Institute at the HSE Faculty of Computer Science have developed a new compression method for large language models such as GPT and LLaMA that reduces their size by 25–36% without additional training or significant loss of accuracy. This is the first approach to use mathematical transformations—specifically, rotations of model weights—to make models more amenable to compression with structured matrices. The study results have been published in ACL Findings 2025. The code is available on GitHub.
HSE Scientists Train Neural Network to 'Hear' Faults in Electric Motors
Researchers at the AI and Digital Science Institute of the HSE Faculty of Computer Science have developed a new method—the Signature-Guided Data Augmentation (SGDA) framework—that achieves 99% accuracy in motor fault detection and 86% accuracy in fault classification. The application of this approach can reduce industrial equipment repair costs, minimise downtime, and improve production safety. The study results have been published in Engineering Applications of Artificial Intelligence.
New Neural Network for Science and Innovation Being Developed at HSE University
HSE researchers are training large language models (LLMs) to understand Russian-language scientific terminology while improving their energy efficiency. The adapted model runs 2.7 times faster and requires 73% less memory than the original open model, allowing it to operate on more affordable hardware. The programme has passed state registration.
HSE FCS Researchers Showcase AI and Bioinformatics Breakthroughs at ICLR 2026
Researchers from the AI and Digital Science Institute at the HSE Faculty of Computer Science, along with students from the AI360: Artificial Intelligence Engineering track of the Applied Mathematics and Information Science bachelor’s programme, took part in ICLR, one of the world’s most prestigious international conferences on machine learning and representation learning. This year’s event was held in Rio de Janeiro, Brazil.
The Future of Cardiogenetics Lies in Artificial Intelligence
Researchers from the AI and Digital Science Institute at the HSE Faculty of Computer Science have developed a program capable of analysing regions of the human genome that were previously inaccessible for accurate interpretation in genetic testing. The program adapts large generative AI (GenAI) models for cardiogenetics to predict how specific mutations affect the function of individual genes.
HSE and Yandex Propose Method to Speed Up Neural Networks for Image Generation
A team of scientists at HSE FCS and Yandex Research has proposed a method that reduces computational costs and accelerates text-to-image generation in diffusion models without compromising quality. These models currently set the standard for text-to-image generation, but their use is limited by high computational loads, the company said in a statement.
A Trap for the Advanced Student: How to Break the Habit of Blindly Trusting Neural Networks
Andrei Ternikov, Associate Professor at the St Petersburg School of Economics and Management at HSE University–St Petersburg, has developed a method for conducting online exams that significantly limits students’ ability to use ChatGPT and other AI models to obtain correct answers. Andrei Ternikov spoke to the HSE News Service about his approach—which won the HSE University Autumn Educational Innovation Competition, received an Alfa Future grant, and was presented at an international conference in Japan.
HSE Researchers Train Neural Network to Predict Protein–Protein Interactions More Accurately
Scientists at the AI and Digital Science Institute of the HSE Faculty of Computer Science have developed a model capable of predicting protein–protein interactions with 95% accuracy. GSMFormer-PPI integrates three types of protein data (including information about protein surface properties) to analyse relationships between proteins, rather than simply combining datasets as in previous models. The solution could accelerate the discovery of disease molecular mechanisms, biomarkers, and potential therapeutic targets. The paper has been published in Scientific Reports.
Human Intuition Proves Stronger than Algorithms: Game Theory Tournament Held at HSE University in Perm
Researchers from the International Laboratory of Intangible-driven Economy (Perm) and the HSE Laboratory of Sports Studies, together with mathematician and science populariser Alexey Savvateev, organised a game theory tournament entitled ‘The Election Race.’ Participants competed both against one another and against artificial intelligence. For now, humans have managed to gain the upper hand and propose more effective strategies.
Educational Programmes on Robotics and Neural Network Technologies Launch at HSE University’s Faculty of Computer Science
Every year, in response to IT industry demands, the Higher School of Economics Faculty of Computer Science launches new educational programmes while updating existing ones. In 2026, the faculty introduced Bachelor’s and Master’s degree programmes in robotics for the first time.